[Crib-list] SPEAKERS: Lothar Wenzel and Darren Schmidt (National Instruments) -- Computational Research in Boston Seminar -- Friday, 06/01/2007 -- TIME: 12:30 PM -- LOCATION: Room 32-141 (Stata Center)

[Shirley Entzminger]

 			COMPUTATIONAL RESEARCH in BOSTON SEMINAR

Date:		FRIDAY, JUNE 1, 2007
Time:		12:30 PM
Location:	Building 32, Room 141 (Stata Center)

Pizza and beverages will be provided at 12:15 PM.


Title:		ATTACKING PROCESSOR ARCHITECTURES FROM TWO
 		MATHEMATICAL ANGLES


Speakers:	LOTHAR WENZEL and DARREN SCHMIDT
 		National Instruments


ABSTRACT:

In the past decade, the evolution of processor architectures has placed 
exceptional demands on the deployment of mathematical algorithms. 
Portable devices contain new more powerful embedded processors making it 
possible to solve more advanced mathematical problems.  The increased use 
of DSPs and FPGAs requires both specialized libraries and tools for 
developing algorithms for these targets.  Now, with the move to multi-core 
processors in mainstream PCs, the numeric libraries optimized for single 
core processors struggle to make use of the additional processing 
resources.  In the worst cases, the performance of these libraries 
degrades on multi-core systems due to data dependencies and communication 
overhead.

Recognizing these challenges, National Instruments (NI) is working on two 
fronts to make the development and deployment of numeric algorithms easier 
for the math and engineering communities.  First, NI has joined with 
vendors in the mathematics industry (INRIA, MapleSoft, and PTC) and 
scientist/engineers in academia, to form the Numerical Mathematics 
Consortium (NMC).  The NMC is defining the fundamental mathematical 
components of math algorithms used in a wide range of applications.  This 
initiative follows the successes of prior de-facto standards, such as BLAS 
and LAPACK, and defines the next generation of mathematical functions 
found in almost all general-purpose math packages.

The NMC's approach to the standard is significantly different from recent 
standards efforts.  By specifying function semantics and not syntax, the 
NMC's function definitions are applicable to many mathematical arenas. 
They provide a solid foundation for math algorithm development and allow 
vendors to promote their programming paradigm which may target specialized 
hardware.  This approach reduces the learning curve for both academia and 
industry by supplying a uniform, consistent set of math definitions for 
fundamental functions.  For those wishing to develop optimal code 
solutions for a specific processor, the NMC defines the basic set of math 
functions needed to support algorithm development on any platform.

While NI works with those in the NMC to bridge the gap between present-day 
algorithm development and tomorrow's architecture, we are also committed 
to solving present-day engineering problems for real world, real-time 
applications.  The availability of low-cost multi-core systems enables 
LabVIEW, NI's graphical system design tool, to combine sophisticated data 
acquisition systems with demanding numerical tasks.  In a typical 
scenario, information about a system is based on direct or derived 
measurements and the acquired data is used to solve linear or even 
nonlinear elliptic partial differential equations.  The results generated 
by the PDE-solver might be used as feedback to the running process.  Such 
a system can be very demanding from a real-time standpoint and might 
require loop-times in the 1 ms range.

To comply with such specifications, multi-core architectures and other 
techniques such as FPGA-based components and high-speed networking are 
supported by LabVIEW.  We provide benchmarks for specific elliptic PDE 
solvers based on 8- and 16-core machines using standard quad-core 
processors where multi-board deployments require fast networking.  We also 
report multi-core performance numbers for more elementary operations such 
as FFT, DST and matrix operations.

You can find more information on the NMC at http://www.numath.org and on 
NI's LabVIEW product line at http://www.ni.com/labview.

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Massachusetts Institute of Technology
Cambridge, MA  02139

http://www-math.mit.edu/crib

For information on CRiB, contact:

Alan Edelman:  edelman at math.mit.edu
Steven G. Johnson:  stevenj at math.mit.edu
Jeremy Kepner:  kepner at ll.mit.edu